forked from 0xWheatyz/SPARC
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-118
@@ -7,131 +7,86 @@ Semiconductor Patent & Analytics Report Core -- development priorities.
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SPARC is a patent analysis platform with a working end-to-end pipeline:
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SPARC is a patent analysis platform with a working end-to-end pipeline:
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Python/FastAPI backend, React/TypeScript frontend, PostgreSQL for persistence
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Python/FastAPI backend, React/TypeScript frontend, PostgreSQL for persistence
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and caching, Docker Compose for local development, and Gitea Actions CI/CD for
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and caching, Docker Compose for local development, and Gitea Actions CI/CD for
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image builds and testing. Core features include patent retrieval via SerpAPI,
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image builds. Core features (patent retrieval via SerpAPI, PDF parsing, LLM
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PDF parsing, LLM analysis via OpenRouter (multi-model: Claude, GPT-4o, Gemini,
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analysis via OpenRouter/Claude, batch processing, JWT authentication, analytics
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Llama), batch processing, JWT authentication, analytics dashboard with patent
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dashboard) are all implemented and functional.
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trend charts, scheduled recurring analysis with alerting, webhook notifications
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(Slack/Discord), CSV and PDF export, S3/MinIO storage, side-by-side company
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comparison, and dark mode.
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---
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## Completed
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Items that have been implemented and merged into main.
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### Security hardening
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- ~~Rotate default JWT secret.~~ Startup check refuses to start with the
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default secret in non-development environments.
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- ~~CORS allow-origins are hardcoded.~~ Allowed origins are now configurable
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via environment variable.
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- ~~Database credentials in docker-compose.yml.~~ Compose references `.env`
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for sensitive values.
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### Error handling and resilience
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- ~~`get_db_client()` creates a new `DatabaseClient` on every call.~~ Refactored
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to a shared pooled singleton initialized at startup.
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- ~~No rate limiting on auth endpoints.~~ Rate limiting middleware added to
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`/auth/login` and `/auth/register`.
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### Test coverage
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- ~~API tests bypass authentication.~~ JWT auth integration tests added (33
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cases covering registration, login, protected routes, token refresh, and
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admin-only endpoints).
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- ~~No test stage in CI.~~ Gitea Actions workflow now runs `pytest` and gates
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the build.
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- ~~No linting or type checking in CI.~~ `ruff` (Python) and `tsc --noEmit`
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(TypeScript) added to CI pipeline.
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### Backend
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- ~~Add structured logging.~~ Python `logging` module used throughout.
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- ~~Make LLM model configurable.~~ `MODEL` environment variable accepted;
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multi-model support with per-analysis selection (GPT-4o, Gemini, Claude,
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Llama).
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- ~~SERP cache TTL hardcoded.~~ `SERP_CACHE_TTL_HOURS` exposed as env var.
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- ~~Patent PDF storage.~~ S3/MinIO object storage backend added alongside
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local filesystem. Volume mount requirement documented.
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- ~~`analyze_single_patent` assumes local file.~~ Auto-download from cached
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metadata link integrated.
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- ~~`Patent.patent_id` typed as `int`.~~ Fixed to `str`.
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### Frontend
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- ~~No loading/error states.~~ Skeleton loaders and error states added to
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Batch and Analytics pages.
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- ~~No dark mode.~~ Full dark mode support with theme-aware chart colors.
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- ~~Missing lockfile.~~ `package-lock.json` committed.
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### Features (formerly P3)
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- ~~Export analysis reports.~~ CSV and PDF export endpoints implemented.
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- ~~Comparison view.~~ Side-by-side company patent portfolio comparison added.
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- ~~Scheduled/recurring analysis.~~ APScheduler-based periodic re-analysis
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with configurable interval and change-threshold alerting.
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- ~~Webhook/notification support.~~ Slack, Discord, and generic HTTP POST
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webhooks with retry logic.
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- ~~Multi-model support.~~ Model picker in Analysis and Batch pages; backend
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allow-list validation.
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- ~~Patent trend charts.~~ Filing frequency and category distribution
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visualizations added to Analytics page.
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- ~~OpenAPI client generation.~~ TypeScript API client auto-generated from
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FastAPI spec with CI freshness check.
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---
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---
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## P1 -- High Priority
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## P1 -- High Priority
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These items address correctness, reliability, and coverage gaps that should be
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These items address correctness, security, and reliability gaps that should be
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resolved before broader production use.
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resolved before broader production use.
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### Resilience
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### Security hardening
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- **`_jobs` dict is in-memory only.** Job state is lost on API restart.
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- **Rotate default JWT secret.** `auth.py` ships a fallback
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Persist job status in PostgreSQL or Redis so async batch results survive
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`sparc-secret-key-change-in-production` that will be used if `JWT_SECRET` is
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restarts.
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unset. Add a startup check that refuses to start with the default secret in
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non-development environments.
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- **CORS allow-origins are hardcoded.** `api.py` only permits
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`localhost:3000` and `localhost:5173`. Make the allowed origins configurable
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via environment variable so the dashboard works when deployed behind a real
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domain.
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- **Database credentials in docker-compose.yml.** The compose file embeds
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`postgres:postgres` in plain text. Reference a `.env` file or Docker secrets
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instead.
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### Test coverage gaps
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### Error handling and resilience
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- **Export endpoint tests.** The CSV and PDF export endpoints (`/export/`)
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- **`get_db_client()` in `auth.py` creates a new `DatabaseClient` on every
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lack test coverage. Add tests covering auth, success, 404, and edge cases.
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call.** This bypasses the connection pool and can exhaust database
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*(Issue #1655)*
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connections under load. Refactor to share a single pooled client.
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- **Tracked company admin endpoint tests.** The `/admin/tracked` CRUD
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- **`_jobs` dict is in-memory only.** Job state is lost on API restart. Persist
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endpoints and scheduler integration lack test coverage. *(Issue #1656)*
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job status in PostgreSQL or Redis so async batch results survive restarts.
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- **No rate limiting on auth endpoints.** `/auth/login` and `/auth/register`
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are unprotected against brute-force or abuse. Add rate limiting middleware.
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### Test coverage for auth and admin
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- The existing API tests (`tests/test_api.py`) bypass authentication entirely.
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Add tests that exercise the JWT flow: registration, login, protected-route
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access, token refresh, and admin-only endpoints.
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---
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---
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## P2 -- Medium Priority
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## P2 -- Medium Priority
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Improvements to reliability, test coverage, and code quality.
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Improvements to usability, performance, and developer experience.
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### Test coverage
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### Backend
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- **Webhook integration tests.** The retry logic, Slack/Discord payload
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- **Add structured logging.** Replace `print()` calls throughout `analyzer.py`,
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format, and multi-URL dispatch in `webhooks.py` need test coverage.
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`serp_api.py`, and `llm.py` with Python `logging` so log levels and
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*(Issue #1657)*
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formatting are consistent.
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- **S3/MinIO storage backend tests.** `storage.py` has local filesystem tests
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- **Make LLM model configurable.** `llm.py` hardcodes
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but no unit tests for the S3 backend (read, write, exists, delete,
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`anthropic/claude-3.5-sonnet`. Accept a `MODEL` environment variable to allow
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error handling). *(Issue #1660)*
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switching models without code changes.
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- **`analyze_single_patent` auto-download path tests.** The auto-download
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- **SERP cache TTL is hardcoded to 24 hours.** Expose `SERP_CACHE_TTL_HOURS`
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fallback (cache lookup, PDF download, FileNotFoundError) in
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as an environment variable in `config.py`.
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`analyzer.py` lacks test coverage. *(Issue #1661)*
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- **Patent PDF storage.** PDFs are saved to a local `patents/` directory. For
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containerized deployments, consider object storage (S3/MinIO) or at minimum
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document the volume mount requirement more prominently.
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- **`analyze_single_patent` assumes local file path.** The method constructs
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`patents/{patent_id}.pdf` and reads from disk, but does not download the PDF
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first. Either integrate the download step or document the prerequisite.
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- **`Patent.patent_id` typed as `int` in `types.py` but used as `str`
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everywhere.** Fix the type annotation to `str`.
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### Code quality
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### Frontend
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- **Scheduler creates its own DatabaseClient.** `scheduler.py` bypasses the
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- **No loading/error states on several pages.** The Batch and Analytics pages
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application-level pooled client, creating a new connection on every tick.
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would benefit from skeleton loaders and user-friendly error messages.
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Refactor to use `get_db_client()`. *(Issue #1658)*
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- **No dark mode.** Tailwind is configured but no dark variant is applied.
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- **Missing `package-lock.json` or `pnpm-lock.yaml`.** The frontend has no
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lockfile committed, leading to non-reproducible builds.
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### API improvements
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### CI/CD
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- **API pagination.** The `/analyze/batch` and `/jobs` endpoints could benefit
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- **No test stage in the Gitea Actions workflow.** `build.yaml` builds and
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from cursor-based pagination for large result sets.
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pushes images but never runs `pytest`. Add a test job that gates the build.
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- **Request validation improvements.** Add stricter input validation for
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- **No linting or type checking.** Add `ruff` (Python) and `tsc --noEmit`
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company names (disallow special characters, enforce length limits).
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(TypeScript) to CI.
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---
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---
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@@ -139,20 +94,23 @@ Improvements to reliability, test coverage, and code quality.
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Lower-urgency enhancements and future features.
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Lower-urgency enhancements and future features.
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- **Historical analysis diffing.** Show what changed between two analysis runs
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- **Export analysis reports.** Allow users to download analysis results as PDF
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for the same company, highlighting new patents and score shifts.
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or CSV from the dashboard.
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- **Patent classification tagging.** Automatically tag patents by technology
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- **Comparison view.** Side-by-side comparison of two companies' patent
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domain (AI, semiconductors, materials science) using LLM classification.
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portfolios.
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- **User-level API keys.** Allow users to generate personal API keys for
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- **Scheduled/recurring analysis.** Periodically re-analyze tracked companies
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programmatic access without JWT token refresh.
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and alert on significant changes.
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- **Batch export.** Export analysis results for multiple companies at once as
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- **Webhook/notification support.** Send alerts (Slack, Discord, email) when
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a ZIP archive.
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batch jobs complete or when a company's innovation score changes
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- **Rate limiting dashboard.** Surface rate limit status and usage statistics
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significantly.
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in the admin panel.
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- **Multi-model support.** Let users choose between LLM providers per analysis
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- **Async webhook delivery.** Move webhook delivery to a background task queue
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(e.g., GPT-4o, Gemini, Claude) and compare outputs.
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(e.g., Celery, arq) to avoid blocking the scheduler.
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- **Patent trend charts.** Visualize patent filing frequency and technology
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- **Multi-tenant support.** Scope analysis results and tracked companies per
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category distribution over time in the Analytics page.
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user or organization.
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- **API pagination.** The `/analyze/batch` and `/jobs` endpoints could benefit
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from cursor-based pagination for large result sets.
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- **OpenAPI client generation.** Auto-generate the TypeScript API client from
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the FastAPI OpenAPI spec to keep frontend types in sync.
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---
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---
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+12
-7
@@ -2,14 +2,17 @@
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Uses APScheduler to periodically re-analyze tracked companies and
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Uses APScheduler to periodically re-analyze tracked companies and
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detect significant changes in patent counts.
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detect significant changes in patent counts.
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The scheduler reuses the application-level pooled DatabaseClient
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(from ``SPARC.auth``) instead of creating its own connection, which
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avoids exhausting the database connection pool under load.
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"""
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"""
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import logging
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import logging
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import os
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import os
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from SPARC import config
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from SPARC.analyzer import CompanyAnalyzer
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from SPARC.analyzer import CompanyAnalyzer
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from SPARC.database import DatabaseClient
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from SPARC.auth import get_db_client
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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@@ -21,10 +24,13 @@ CHANGE_THRESHOLD_PERCENT = int(os.getenv("CHANGE_THRESHOLD_PERCENT", "20"))
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def run_scheduled_analysis() -> None:
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def run_scheduled_analysis() -> None:
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"""Re-analyze all tracked companies and check for significant changes."""
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"""Re-analyze all tracked companies and check for significant changes.
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db = DatabaseClient(config.database_url)
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db.connect()
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Uses the shared pooled DatabaseClient from ``SPARC.auth.get_db_client()``
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db.initialize_schema()
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rather than creating a disposable connection, so the scheduler participates
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in the same connection pool as the rest of the application.
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"""
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db = get_db_client()
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tracked = db.list_tracked_companies()
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tracked = db.list_tracked_companies()
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if not tracked:
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if not tracked:
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@@ -74,7 +80,6 @@ def run_scheduled_analysis() -> None:
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except Exception as e:
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except Exception as e:
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logger.error("Error analyzing tracked company %s: %s", name, e)
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logger.error("Error analyzing tracked company %s: %s", name, e)
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db.close()
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logger.info("Scheduled analysis complete")
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logger.info("Scheduled analysis complete")
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Block a user